Lead the design, implementation, and maintenance of cloud infrastructure on GCP, optimize CI/CD pipelines, manage Kubernetes clusters, and enhance system reliability and observability solutions.
LSports is the leading global provider of sports data, dedicated to revolutionizing the industry through innovative solutions. We excel in sports data collection and analysis, advanced data management, and cutting-edge services like AI-based sports tips and high-quality sports visualization. As the sports data industry continues to grow, LSports remains at the forefront, delivering real-time solutions.
If you're passionate about both sports and technology and want to drive the sports-tech and data industries into the future, we invite you to join the team! We are looking for a highly motivated Senior DevOps Engineer.
Responsibilities:
Infrastructure & Platform Engineering
- Cloud Architecture: Design and operate high-scale, production-grade infrastructure primarily on GCP (leveraging GCE, Cloud SQL, and networking).
- Kubernetes Mastery: Own the lifecycle of GKE clusters, including advanced networking, security hardening, and scaling strategies.
- IaC & Automation: Architect modular infrastructure using Terraform or Pulumi and manage deployments via Helm.
- Data & Messaging: Support high-throughput data platforms, including Databricks, Confluent Kafka, and RabbitMQ.
Continuous Delivery & GitOps
- GitOps Excellence: Standardize deployments using ArgoCD for automated, declarative environment synchronization.
- CI/CD Innovation: Build and optimize GitHub Actions workflows to minimize lead time for changes.
- Developer Enablement: Reduce friction by building internal scripts and automation in Python and Bash that empower dev teams.
Reliability & AI Integration
- AI-Augmented Workflow: Integrate AI tools (Copilot, ChatGPT, Claude) into the daily DevOps lifecycle to accelerate scripting, complex troubleshooting, and documentation.
- Observability: Monitor system health with VictoriaMetrics and Datadog to ensure actionable alerting and high visibility.
- Incident Response: Participate in on-call rotations, maintain runbooks, and drive blameless postmortems.
- Experience: 5+ years in DevOps, SRE, or Platform Engineering with a deep focus on GCP and Kubernetes.
- Technical Stack: Proficiency with Terraform/Pulumi, Helm, ArgoCD, and GitHub Actions.
- Data Infrastructure: Hands-on experience managing distributed systems like Kafka/RMQ and data platforms like Databricks.
- Coding: Strong proficiency in Python and Bash for automation and tool development.
- AI-Powered Mindset: Active Practitioner: Demonstrated ability to use AI tools (GitHub Copilot, LLMs) to write better code faster, debug complex infrastructure issues, and generate high-quality documentation.
- Prompt Engineering: Ability to leverage AI to "rubber-duck" architectural decisions and automate repetitive "toil."
- Operational Excellence: Experience with observability stacks (Datadog/VictoriaMetrics) and managing stateful workloads in cloud environments.
Nice to Have:
- MLOps: Experience building and scaling production-grade AI/ML pipelines.
- FinOps: A proven track record of optimizing GCP spend and resource efficiency.
- TestOps: Expertise in integrating automated testing (performance/security) into the CI/CD gatekeeping process.
Top Skills
Argocd
Bash
Ci/Cd
Datadog
GCP
Github Actions
Gke
Helm
Kafka
Kubernetes
MongoDB
MySQL
Postgres
Python
RabbitMQ
Redis
Terraform
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